The purpose of this thesis was to characterize the artifacts and nd ways to reduce them during data acquisition and in o²ine analysis. The results show that the artifact is highest in anterior and lateral areas and that the high amplitude and long duration of the artifact in lateral areas makes removing it a challenging task.

Two methods of o²ine artifact removal were evaluated for the high-artifact data. Independent component analysis (ICA) and multiple-source modeling were able to reduce the artifact, but also arected the brain signal during or after the artifact.